The prior art includes various technologies for uniquely identifying an individual person in accordance with an examination of particular attributes of either the person's interior or exterior eye. The prior art also includes a technology for eye tracking image pickup apparatus for separating noise from feature portions, such as that disclosed in U.S. Pat. No. 5,016,282, issued to Tomono et al. on May 14, 1991. One of these prior-art technologies involves the visual examination of the particular attributes of the exterior of the iris of at least one of the person's eyes. In this regard, reference is made to U.S. Pat. No. 4,641,349 issued to Flom et al. on Feb. 3, 1987, U.S. Pat. No. 5,291,560, issued to Daugman on Mar. 1, 1994, and to Daugman's article "High Confidence Visual Recognition of Persons by a Test of Statistical Independence", which appears on pages 1148-1161 of the IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 15, No. 11, Nov. 1993. As made clear by the aforesaid patents and article, the visible texture of a person's iris can be used to distinguish one person from another with great accuracy. Thus, iris recognition may be used for such purposes as controlling access to a secure facility or an Automated Transaction Machine (ATM) for dispensing cash, by way of examples. An iris recognition system involves the use of an imager to video image the iris of each person attempting access and computer-vision image processing means for comparing this iris video image with a reference iris image on file in a database. For instance, the person attempting access may first enter a personal identification number (PIN), thereby permitting the video image of the iris of that person to be associated with his or her reference iris image on file. In addition, an iris recognition system is useful for such purposes as medical diagnostics in the medical examination of the exterior eye.
From a practical point of view, there are problems with prior-art iris recognition systems and methods.
First, previous approaches to acquiring high quality images of the iris of the eye have: (i) an invasive positioning device (e.g., a head rest or bite bar) serving to bring the subject of interest into a known standard configuration; (ii) a controlled light source providing standardized illumination of the eye, and (iii) an imager serving to capture the positioned and illuminated eye. There are a number of limitations with this standard setup, including: (a) users find the physical contact required for positioning to be unappealing, and (b) the illumination level required by these previous approaches for the capture of good quality, high contrast images can be annoying to the user.
Second, previous approaches to localizing the iris in images of the eye have employed parameterized models of the iris. The parameters of these models are iteratively fit to an image of the eye that has been enhanced so as to highlight regions corresponding to the iris boundary. The complexity of the model varies from concentric circles that delimit the inner and outer boundaries of the iris to more elaborate models involving the effects of partially occluding eyelids. The methods used to enhance the iris boundaries include gradient based edge detection as well as morphological filtering. The chief limitations of these approaches include their need for good initial conditions that serve as seeds for the iterative fitting process as well as extensive computational expense.
Third, previous approaches to pattern match a localized iris data image derived from the video image of a person attempting to gain access with that of one or more reference localized iris data images on file in a database provide reasonable discrimination between these iris data images., but require extensive computational expense